Detection device, detection system, and detection method

ABSTRACT

A detection device includes a camera, a recognition unit, and a detection unit. The camera acquires image data obtained by capturing surroundings of a vehicle. The recognition unit recognizes switching of signal indication of a traffic signal from the image data. The detection unit detects a dangerous driving degree indicating a degree of dangerous driving done by a driver of the vehicle based on acceleration data of the vehicle acquired after the signal indication is switched.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims priority to and incorporates by referencethe entire contents of Japanese Patent Application No. 2014-241944 filedin Japan on Nov. 28, 2014.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to detection devices, detection systems,and detection methods.

2. Description of the Related Art

Technology for assisting a driver and storing an image(s) in the eventof an accident by utilizing a vehicular camera is conventionally known.Examples of such a driver assist technology utilizing a vehicular camerainclude an automatic braking function of avoiding an obstacle orreducing impact at collision with an obstacle, and an alert functionproviding a warning to maintain a distance from a vehicle ahead and thelike.

Japanese Laid-open Patent Application No. 2014-78071 discloses atechnique of controlling whether or not to store an image(s) captured bya camera mounted on a vehicle in a driving recorder depending on anacceleration of the vehicle detected by an acceleration sensor.

However, the conventional technique is disadvantageous in that it isdifficult to detect dangerous driving done by a driver when signalindication of a traffic signal is switched.

Therefore, there is a need for a detection device, a detection system,and a detection method capable of detecting dangerous driving done by adriver when signal indication of a traffic signal is switched.

SUMMARY OF THE INVENTION

It is an object of the present invention to at least partially solve theproblems in the conventional technology.

According to an embodiment, a detection device includes a camera, arecognition unit, and a detection unit. The camera acquires image dataobtained by capturing surroundings of a vehicle. The recognition unitrecognizes switching of signal indication of a traffic signal from theimage data. The detection unit detects a dangerous driving degreeindicating a degree of dangerous driving done by a driver of the vehiclebased on acceleration data of the vehicle acquired after the signalindication is switched.

The above and other objects, features, advantages and technical andindustrial significance of this invention will be better understood byreading the following detailed description of presently preferredembodiments of the invention, when considered in connection with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating an example of a vehicle with adetection device of a first embodiment mounted thereon;

FIG. 2 is a diagram illustrating an example of a configuration of thedetection device of the first embodiment;

FIG. 3 is a diagram illustrating an example of image data obtained bycapturing a traffic signal;

FIG. 4 is a diagram illustrating an example of (U,V) distribution of redsignal pixels;

FIG. 5 is a diagram illustrating an example of (U,V) distribution ofgreen signal pixels;

FIG. 6 is a diagram illustrating an example of (U,V) distribution ofyellow signal pixels;

FIG. 7 is a diagram illustrating an example of a green-signal pixelregion extracted by a recognition unit of the first embodiment;

FIG. 8 is a diagram illustrating an example of an expanded pixel regionobtained by the recognition unit of the first embodiment;

FIG. 9 is a diagram illustrating an example of a circular pixel regionextracted by Hough transform performed by the recognition unit of thefirst embodiment;

FIG. 10 is a diagram illustrating an example of a recognition resultregion obtained by the recognition unit of the first embodiment;

FIG. 11 is a diagram illustrating an example of a recognition resultregion recognized by the recognition unit of the first embodiment;

FIG. 12 is a diagram illustrating an example of a dangerous drivingdegree of the first embodiment;

FIG. 13 is a flowchart illustrating an example of a detection methodperformed by the detection device of the first embodiment;

FIG. 14 is a flowchart illustrating an example of a signal recognitionprocess performed by the detection device of the first embodiment;

FIG. 15 is a diagram illustrating an example of a hardware structure ofa camera of the first embodiment;

FIG. 16 is a diagram illustrating an example of a configuration of adetection system according to a second embodiment;

FIG. 17 is a diagram illustrating an example of a configuration of aserver apparatus of the second embodiment; and

FIG. 18 is a diagram illustrating an example of a hardware structure ofthe server apparatus of the second embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Exemplary embodiments of the present invention are described in detailbelow with reference to the accompanying drawings.

First Embodiment

FIG. 1 is a diagram illustrating an example of a vehicle 200 with adetection device 100 according to a first embodiment mounted thereon.The detection device 100 of the first embodiment is installed to awindshield of the vehicle 200 at a position near a rear-view mirror. Thedetection device 100 of the first embodiment detects dangerous drivingdone by a driver when signal indication of a traffic signal 300 isswitched.

FIG. 2 is a diagram illustrating an example of a configuration of thedetection device 100 of the first embodiment. The detection device 100of the first embodiment includes a camera 10, a signal processing unit20, and a communication unit 30. The signal processing unit 20includesan acceleration sensor 21, an interface unit 22, a recognition unit 23,and a detection unit 24.

The camera 10 acquires color image data by capturing the surroundings ofthe vehicle 200. The camera 10 feeds the image data to the interfaceunit 22.

The acceleration sensor 21 acquires acceleration data of the vehicle 200and feeds the acceleration data to the interface unit 22.

Upon receiving the image data from the camera 10, the interface unit 22converts the image data into a data format acceptable by the recognitionunit 23 as consecutive time-series image frames. The interface unit 22feeds the image data having undergone the data-format conversion to therecognition unit 23. Upon receiving the acceleration data from theacceleration sensor 21, the interface unit 22 converts the accelerationdata into a data format acceptable by the detection unit 24. Theinterface unit 22 feeds the acceleration data having undergone thedata-format conversion to the detection unit 24.

Upon receiving the image data from the interface unit 22, therecognition unit 23 recognizes switching of signal indication of thetraffic signal 300 from the image data.

FIG. 3 is a diagram illustrating an example of image data obtained bycapturing the traffic signal 300. The example illustrated in FIG. 3 isan example of image data captured in a situation where signal indicationof the traffic signal 300 is green (hereinafter, “green signal”) andtherefore contains a region 101 representing the green signal of thetraffic signal 300. The recognition unit 23 recognizes switching ofsignal indication of the traffic signal 300 by performing a process ofrecognizing signal indication (hereinafter, “signal recognitionprocess”), which will be described later.

Referring back to FIG. 2, the signal recognition process, by which therecognition unit 23 recognizes switching of signal indication of thetraffic signal 300, is described in detail below. The recognition unit23 converts the image data in the (R,G,B) color space into image data inthe (Y,U,V) color space using Equation (1) below.

$\begin{matrix}{\begin{bmatrix}Y \\U \\V\end{bmatrix} = {\begin{bmatrix}0.299 & 0.587 & 0.114 \\{- 0.147} & {- 0.289} & 0.436 \\0.615 & {- 0.515} & 0.100\end{bmatrix}\begin{bmatrix}R \\G \\B\end{bmatrix}}} & (1)\end{matrix}$

Thereafter, the recognition unit 23 performs an extraction process ofextracting a signal pixel region representing signal indication from theimage data in the (Y,U,V) color space based on (U,V) distributions ofred signal pixels, green signal pixels, and yellow signal pixels and theimage data in the (Y,U,V) color space. An example of (U,V) distributionof the red signal pixels, that of the green signal pixels, and that ofthe yellow signal pixels are respectively described below.

FIG. 4 is a diagram illustrating an example of (U,V) distribution of redsignal pixels. More specifically, FIG. 4 illustrates an example of (U,V)distribution of red signal pixels obtained from image data in the(R,G,B) color space of a plurality of image samples, in each of which ared signal is captured.

FIG. 5 is a diagram illustrating an example of (U,V) distribution ofgreen signal pixels. More specifically, FIG. 5 illustrates an example of(U,V) distribution of green signal pixels obtained from image data inthe (R,G,B) color space of a plurality of image samples, in each ofwhich a green signal is captured.

FIG. 6 is a diagram illustrating an example of (U,V) distribution ofyellow signal pixels. More specifically, FIG. 6 illustrates an exampleof (U,V) distribution of yellow signal pixels obtained from image datain the (R,G,B) color space of a plurality of image samples, in each ofwhich a yellow signal is captured.

Referring back to FIG. 2, more specifically, the recognition unit 23determines whether or not (U,V) values of the image data in the (Y,U,V)color space fall within a range of predetermined thresholds for U (U-minand U-max) and predetermined thresholds for V (V-min and V-max) for eachof the (U,V) distributions illustrated in FIGS. 4 to 6. Thereafter, therecognition unit 23 extracts, from the image data in the (Y,U,V) colorspace, pixels within the threshold range as a signal pixel region.

Specific values of the thresholds for U (U-min and U-max) and thethresholds for V (V-min and V-max) may be determined as desired.However, if the threshold range is excessively large, possibility that apixel not representing signal indication is falsely detected increases.Accordingly, the thresholds are to be set not to cover (U,V) values of apixel not representing signal indication.

FIG. 7 is a diagram illustrating an example of a green-signal pixelregion 102 extracted by the recognition unit 23 of the first embodiment.The green-signal pixel region 102 illustrated in FIG. 7 is smaller insize than the region 101 representing the actual green signal. Morespecifically, FIG. 7 illustrates an example, in which a region thatshould be extracted as a green-signal region is not extracted as greensignal pixels due to influence of noise pixels. The noise pixels mayinclude any one of noise pixels produced by the environment where theimage is captured, noise pixels resulting from characteristics of animaging device, and noise pixels produced by dusts sticking to thesurface of the imaging device. The noise pixels produced by theenvironment where the image is captured are, more specifically, pixelsin a green-signal region, from which light, e.g., sunlight, is reflectedwhen the image of the traffic signal 300 is captured by the camera 10.The noise pixels resulting from characteristics of an imaging deviceare, more specifically, pixels influenced by random noise, for example.

Referring back to FIG. 2, the recognition unit 23 performs an expansionprocess of expanding the signal pixel region. More specifically, therecognition unit 23 expands the signal pixel region into an expandedpixel region by covering each pixel in the signal pixel region with aplurality of pixels. The recognition unit 23 may cover each pixel with,for example, an n×n (n is an integer greater than 0) pixel block. Forexample, if n=7 is given, the recognition unit 23 expands each pixel inthe signal pixel region into an expanded pixel region additionallyincluding 48 (=7×7−1) pixels surrounding the pixel.

FIG. 8 is a diagram illustrating an example of an expanded pixel region103obtained by the recognition unit 23 of the first embodiment. Morespecifically, FIG. 8 illustrates an example, in which the expanded pixelregion 103 containing the region 101 representing the green signal, isobtained by performing the expansion process on the extractedgreen-signal pixel region 102.

Referring back to FIG. 2, the recognition unit 23 performs a shaperecognition process of recognizing the shape of the region representingsignal indication. More specifically, the recognition unit 23 appliesHough transform to the extracted signal pixel region, therebydetermining whether or not a circular pixel region can be extracted fromthe expanded pixel region. If a circular pixel region can be extracted,the recognition unit 23 recognizes that the circular pixel region is aregion representing signal indication of the traffic signal 300. Therecognition unit 23 calculates a rectangular region circumscribing thecircular pixel region and generates recognition data indicating therectangular region as a recognition result region.

FIG. 9 is a diagram illustrating an example of the circular pixel regionextracted by Hough transform by the recognition unit 23 of the firstembodiment. More specifically, FIG. 9 illustrates an example, in whichthe region 101 representing a green signal is extracted as the circularpixel region by applying Hough transform to the green-signal pixelregion 102 (see FIG. 7).

FIG. 10 is a diagram illustrating an example of a recognition resultregion 104 obtained by the recognition unit 23 of the first embodiment.More specifically, FIG. 10 illustrates an example, in which therecognition result region 104 is recognized as a rectanglecircumscribing the region 101 representing the green signal extracted asthe circular pixel region.

FIG. 11 is a diagram illustrating an example of a recognition resultregion 104recognized by the recognition unit 23 of the first embodiment.More specifically, FIG. 11 illustrates an example, in which the greensignal of the traffic signal 300 included in the image data illustratedin FIG. 3 is recognized as the recognition result region 104 containingthe region 101 representing the green signal.

Referring back to FIG. 2, the recognition unit 23 performs adetermination process of determining whether or not switching of signalindication of the traffic signal 300 can be recognized from a pluralityof pieces of recognition data obtained by generating the recognitiondata described above in a time series manner. If the recognition unit 23recognizes that signal indication is switched, the recognition unit 23feeds a request for starting a dangerous-driving detection process tothe detection unit 24.

The detection unit 24 receives the request for starting the detectionprocess from the recognition unit 23 and receives acceleration data fromthe interface unit 22. Upon receiving the request for starting thedetection process from the recognition unit 23, the detection unit 24detects dangerous driving done by a driver of the vehicle 200 based onacceleration data acquired after the signal indication is switched.

More specifically, the detection unit 24 detects dangerous driving doneby the driver of the vehicle 200 based on a dangerous driving degree,which is determined depending on a duration of time between when thesignal indication is switched and when acceleration exceeds a firstthreshold. An example of the dangerous driving degree is describedbelow.

FIG. 12 is a diagram illustrating an example of the dangerous drivingdegree of the first embodiment. More specifically, FIG. 12 illustratesan example of a dangerous driving degree for a situation where signalindication switches from the red signal to the green signal. Durationtime t is a duration of time between when signal indication changes fromred to green and when the acceleration exceeds the first threshold. Thedangerous driving degree indicates a degree of danger of dangerousdriving. The higher the dangerous driving degree, the more dangerous thedriving. For example, when the duration time between when signalindication changes from red to green and when the acceleration exceedsthe first threshold is 3 seconds, the dangerous driving degree is 2.

The dangerous driving degree may be determined as desired depending onwhat type of driving is judged as dangerous. For instance, when making afast start immediately after signal indication changes from red togreen, there is a possibility that a pedestrian is still walking acrossa crosswalk or the like. In the example illustrated in FIG. 12 wheresuch driving is judged most dangerous, the dangerous driving degree isdefined such that the shorter the duration time t, the higher thedangerous driving degree.

Referring back to FIG. 2, the detection unit 24 feedsdangerous-driving-degree information indicating the dangerous drivingdegree to the communication unit 30. Upon receiving thedangerous-driving-degree information from the detection unit 24, thecommunication unit 30 transmits detection information, in whichidentification information, by which a transmission source isidentified, is associated with the dangerous-driving-degree information,to a server apparatus. The identification information, by which thetransmission source is identified, is described below.

The transmission source may be identified on a per-the-vehicle-200 basis(per-the-detection-device-100 basis), or on a per-driver basis. In asituation where the vehicle 200 can be driven by any one of a pluralityof drivers and therefore it is desired to detect dangerous driving on aper-driver basis, the following configuration may be adopted, forexample. That is, before a driver drives the vehicle 200, the detectiondevice 100 identifies the driver and transmits detection informationincluding identification information of the driver to the serverapparatus. An embodiment of a detection system including the serverapparatus will be described later in a second embodiment.

The driver may be identified by any desired method. For example, driveridentification may be made by inserting an ID (identification) card, bywhich the driver is identified, into an ID card slot provided in thedetection device 100 and identifying the driver based on the inserted IDcard. For another example, driver identification may be made by areading unit provided in the detection device 100, which reads an IC(integrated circuit) card, by which the driver is identified, byutilizing a communication standard such as an NFC (near fieldcommunication).

The detection unit 24 described above may be configured to alert thedriver that the driver is making dangerous driving by sound or the likeif the detected dangerous driving degree is higher than a secondthreshold.

A detection method performed by the detection device 100 of the firstembodiment is described below.

FIG. 13 is a flowchart illustrating an example of the detection methodperformed by the detection device 100 of the first embodiment. Therecognition unit 23 receives image data acquired by the camera 10 fromthe interface unit 22 (S1). Thereafter, the recognition unit 23performsthe signal recognition process (S2). Details of the signal recognitionprocess will be described later with reference to FIG. 14.

If switching of signal indication is recognized in the signalrecognition process at S3 (Yes at S3), the detection unit 24 detectsdangerous driving done by a driver of the vehicle 200 based on adangerous driving degree (see FIG.2), which is determined depending onthe duration of time between when the signal indication is switched andwhen acceleration exceeds the first threshold (S4). If switching ofsignal indication is not recognized in the signal recognition process atS3 (No at S3), processing returns to S1.

Thereafter, the communication unit 30 transmits detection information,in which identification information, by which the driver is identified,is associated with dangerous-driving-degree information indicating thedangerous driving degree, to the server apparatus (S5).

The signal recognition process at S2 is described in detail below.

FIG. 14 is a flowchart illustrating an example of the signal recognitionprocess performed by the detection device 100 of the first embodiment.The recognition unit 23 performs the extraction process of extracting asignal pixel region representing signal indication from the image datain the (Y,U,V) color space based on the (U,V) distributions of the redsignal pixels, the green signal pixels, and the yellow signal pixels andthe image data in the (Y,U,V) color space first (S11).

Thereafter, the recognition unit 23 performs the expansion process,described above, of expanding the signal pixel region (S12). Thereafter,the recognition unit 23 performs the shape recognition process,described above, of recognizing the shape of a region representingsignal indication (S13). Thereafter, the recognition unit 23 determineswhether or not switching of signal indication of the traffic signal 300is recognized from the plurality of pieces of recognition data,described above, obtained by the shape recognition process performed atS13 (S14).

A hardware structure of the detection device 100 of the first embodimentis described below.

A hardware structure of the camera 10 is described first.

FIG. 15 is a diagram illustrating an example of the hardware structureof the camera 10 of the first embodiment. The camera 10 of the firstembodiment includes an imaging optical system 201, a mechanical shutter202, a motor driver 203, a CCD (charge coupled device) 204, a CDS(correlated double sampling) circuit 205, an A/D converter 206, atiming-signal generator 207, an image processing circuit 208, an LCD(liquid crystal display) 209, a CPU (central processing unit) 210, a RAM(random access memory) 211, a ROM (read only memory) 212, an SDRAM(synchronous dynamic random access memory) 213, acompression/decompression circuit 214, a memory 215, an operation unit216, and an output I/F 217.

The image processing circuit 208, the CPU 210, the RAM 211, the ROM 212,the SDRAM 213, the compression/decompression circuit 214, the memory215, the operation unit 216, and the output I/F 217 are connected toeach other via a bus 220.

The imaging optical system 201 converges light reflected from a subject.The mechanical shutter 202 is opened a predetermined period of time,thereby causing the light converged by the imaging optical system 201 tobe incident on the CCD 204. The motor driver 203 drives the imagingoptical system 201 and the mechanical shutter 202.

The CCD 204 forms an image of the subject with the light incident on theCCD 204 via the mechanical shutter 202, and feeds analog image datarepresenting the subject image to the CDS circuit 205. Upon receivingthe analog image data from the CCD 204, the CDS circuit 205 removesnoise components from the image data, and feeds the analog image data,from which the noise components are removed, to the A/D converter 206.Upon receiving the analog image data from the CDS circuit 205, the A/Dconverter 206 converts the analog image data into digital image data.The A/D converter 206 feeds the digital image data to the imageprocessing circuit 208. The timing-signal generator 207 controlsoperation timing of the CCD 204, the CDS circuit 205, and the A/Dconverter 206 by transmitting timing signals to the CCD 204, the CDScircuit 205, and the A/D converter 206 in accordance with controlsignals fed from the CPU 210.

Upon receiving the digital image data from the A/D converter 206, theimage processing circuit 208 performs image processing on the digitalimage data using the SDRAM 213. Examples of the image processing includeCrCb conversion, white balancing, contrast correction, edge enhancement,and color conversion. The white balancing is image processing ofadjusting color intensities of image data. The contrast correction isimage processing of adjusting contrast of image data. The edgeenhancement is image processing of adjusting sharpness of image data.The color conversion is image processing of adjusting hue of image data.

The image processing circuit 208 feeds image data having undergone theimage processing described above to the LCD 209 or thecompression/decompression circuit 214. The LCD 209 is a liquid crystaldisplay for displaying the image data received from the image processingcircuit 208.

The CPU 210 controls operations of the camera 10 by executing programinstructions. The RAM 211 is a work area used by the CPU 210 inexecuting the program instructions and is a readable and writablestorage area used to store various types of data and the like. The ROM212 is a read-only storage area where the program instructions to beexecuted by the CPU 210 and the like are to be stored.

The SDRAM 213 is a storage area where image data is temporarily storedwhen the image processing circuit 208 performs image processing on theimage data.

Upon receiving image data from the image processing circuit 208, thecompression/decompression circuit 214 compresses the image data. Thecompression/decompression circuit 214 stores the compressed image datain the memory 215. Furthermore, upon receiving image data from thememory 215, the compression/decompression circuit 214 decompresses theimage data. The compression/decompression circuit 214 temporarily storesthe decompressed image data in the SDRAM 213. The memory 215 temporarilystores therein the compressed image data.

The operation unit 216 accepts an operation from a user of the camera10. For example, the operation unit 216 accepts an operation of storingimage data displayed on the LCD 209 in the memory 215. The output I/F217 is an interface for transmitting image data from the camera 10 tothe signal processing unit 20.

The interface unit 22, the recognition unit 23, and the detection unit24 of the signal processing unit 20 described above with reference toFIG. 2 may be implemented either in hardware as a signal processingboard (i.e., a signal processing circuit) or in software (programinstructions) executed by the CPU 210 of the camera 10.

The program instructions to be executed by the detection device 100 (or,more specifically, the CPU 210) of the first embodiment may be providedas a computer program product recorded in a non-transitorycomputer-readable storage medium such as a CD-ROM, a memory card, aCD-R, or a DVD (digital versatile disk) as an installable file or anexecutable file.

The program instructions to be executed by the detection device 100 ofthe first embodiment may be configured to be stored in a computerconnected to a network such as the Internet and provided by beingdownloaded via the network. The program instructions to be executed bythe detection device 100 of the first embodiment may be configured to beprovided via a network such as the Internet without being downloaded.

The program instructions of the detection device 100 of the firstembodiment may be configured to be provided as being installed in theROM 212 or the like in advance.

When the interface unit 22, the recognition unit 23, the detection unit24, and the like are to be implemented in the program instructionsexecuted by the detection device 100 of the first embodiment, theinterface unit 22, the recognition unit 23, the detection unit 24, andthe like may preferably be implemented on the RAM 211 by the CPU 210 byloading the program instructions from the ROM 212, the storage medium,or the like and executing the program instructions.

If acceleration data can be acquired from a network CAN (controller areanetwork) mounted on the vehicle 200, the acceleration sensor 21 may beomitted from the signal processing unit 20.

As described above, in the detection device 100 of the first embodiment,the recognition unit 23 recognizes switching of signal indication of thetraffic signal 300 from image data. The detection unit 24 detects adangerous driving degree, which indicates a degree of danger ofdangerous driving done by a driver of the vehicle 200, based onacceleration data of the vehicle 200 acquired after the signalindication is switched. The detection device 100 of the first embodimentcan thus detect dangerous driving done by the driver when signalindication of the traffic signal 300 is switched.

Second Embodiment

The second embodiment is described below.

FIG. 16 is a diagram illustrating an example of a configuration of adetection system 400 according to the second embodiment. The detectionsystem 400 of the second embodiment includes a detection device 100-1, adetection device 100-2, . . . ,and a detection device 100-N (N is aninteger greater than 0), and a server apparatus 600. The detectiondevice 100-1, the detection device 100-2, . . . , and the detectiondevice 100-N, and the server apparatus 600 are connected to each othervia a network 500. The network 500 may be the Internet, for example. Thedetection device 100-1, the detection device 100-2, . . . , and thedetection device 100-N are respectively mounted on a vehicle 200-1, avehicle 200-2, . . . , and a vehicle 200-N, which are not illustrated inFIG. 16. Hereinafter, each of the detection device 100-1, the detectiondevice 100-2, . . . , and the detection device 100-N is simplycollectively referred to as the detection device 100.

The detection device 100 of the second embodiment is identical inconfiguration to that of the first embodiment (see FIG. 2). Thecommunication unit 30 of the detection device 100 transmits, to theserver apparatus 600, detection information, in which driver's dangerousdriving degree detected using the method described in the firstembodiment is associated with identification information, by which atransmission source is identified. The second embodiment is described onan assumption that the identification information, by which thetransmission source is identified, is identification information of thedriver.

FIG. 17 is a diagram illustrating an example of a configuration of theserver apparatus 600 of the second embodiment. The server apparatus 600of the second embodiment includes a communication unit 61, a storageunit 62, and an evaluation unit 63. Upon receiving the detectioninformation from the detection device 100, the communication unit 61stores the detection information in the storage unit 62. The evaluationunit 63 evaluates dangerous driving of the driver based on the detectioninformation stored in the storage unit 62. In a situation wheredangerous driving degree is defined, for example, as illustrated in FIG.12, the evaluation unit 63 evaluates driver's dangerous driving using asum of dangerous driving degrees or an average value of the driver'sdangerous driving degrees (which is (the sum of the dangerous drivingdegrees)/(the number of detection information pieces each containing theidentification information of the driver)) calculated for each ofidentification information pieces, by which each driver is identified.The larger the sum of the dangerous driving degrees or the average valueof the driver's dangerous driving degrees, the more dangerous thedriver's driving.

A hardware structure of the server apparatus 600 of the secondembodiment is described below.

FIG. 18 is a diagram illustrating an example of the hardware structureof the server apparatus 600 of the second embodiment. The serverapparatus 600 of the second embodiment includes a control device 71, amain storage device 72, an auxiliary storage device 73, a display device74, an input device 75, and a communication device 76. The controldevice 71, the main storage device 72, the auxiliary storage device 73,the display device 74, the input device 75, and the communication device76 are connected to each other via a bus 80.

The control device 71 executes program instructions loaded from theauxiliary storage device 73 into the main storage device 72. The mainstorage device 72 is a memory such as a ROM or a RAM. The auxiliarystorage device 73 is an HDD (hard disk drive), an optical drive, or thelike. The storage unit 62 illustrated in FIG. 17 corresponds to the mainstorage device 72 and the auxiliary storage device 73.

The display device 74 displays a status of the server apparatus 600 andthe like. The device 74 is an LCD, for example. The input device 75 isan interface for operating the server apparatus 600. The input device 75is a keyboard, a mouse, and the like, for example. The communicationdevice 7 is an interface for connecting to the network 500.

The program instructions to be executed in the server apparatus 600 ofthe second embodiment may be provided as a computer program productrecorded in a non-transitory computer-readable storage medium such as aCD-ROM, a memory card, a CD-R, or a DVD as an installable file or anexecutable file.

The program instructions to be executed in the server apparatus 600 ofthe second embodiment may be configured to be stored in a computerconnected to the network 500 such as the Internet and provided by beingdownloaded via the network. The program instructions to be executed inthe server apparatus 600of the second embodiment may be configured to beprovided via the network 500 such as the Internet without beingdownloaded.

The program instructions of the server apparatus 600 of the secondembodiment may be configured to be provided as being installed in theROM of the main storage device 72 or the like in advance.

The program instructions to be executed in the server apparatus 600 ofthe second embodiment are configured in modules including thecommunication unit 61 and the evaluation unit 63 illustrated in FIG. 16described above. The communication unit 61 and the evaluation unit 63are loaded into the main storage device 72 by the control device 71 byreading out the program instructions from the storage medium andexecuting the program instructions. Hence, the communication unit 61 andthe evaluation unit 63 are generated on the main storage device 72. Apart or all of the communication unit 61 and the evaluation unit 63illustrated in FIG. 16 may be implemented in hardware such as an ICrather than in software.

As described above, in the detection system 400 of the secondembodiment, the recognition unit 23 recognizes switching of signalindication of the traffic signal 300 from image data. The detection unit24 detects a dangerous driving degree done by a driver of the vehicle200 based on acceleration data of the vehicle 200 acquired after thesignal indication is switched. The evaluation unit 63 evaluates drivingof the driver based on the driver's dangerous driving degree stored inthe storage unit 62.

The detection system 400 of the second embodiment can thus evaluatedriver's driving based on the driver's dangerous driving degree detectedby the detection device 100. A result of the evaluation of the driver'driving obtained by the detection system 400 of the second embodimentcan be utilized in calculation of automobile-insurance fee of the driverand the like.

The recognition unit 23, the detection unit 24, the storage unit 62, andthe evaluation unit 63 of the detection system 400 may be implemented oneither the detection device 100 or the server apparatus 600. Forexample, the storage unit 62 and the evaluation unit 63 may beimplemented on the detection device 100.

According to an aspect of the present invention, it is possible todetect dangerous driving done by a driver when signal indication of atraffic signal is switched.

Although the invention has been described with respect to specificembodiments for a complete and clear disclosure, the appended claims arenot to be thus limited but are to be construed as embodying allmodifications and alternative constructions that may occur to oneskilled in the art that fairly fall within the basic teaching herein setforth.

What is claimed is:
 1. A detection device comprising: a cameraconfigured to acquire image data obtained by capturing surroundings of avehicle; a recognition unit configured to recognize switching of signalindication of a traffic signal from the image data; and a detection unitconfigured to detect a dangerous driving degree indicating a degree ofdangerous driving done by a driver of the vehicle based on accelerationdata of the vehicle acquired after the signal indication is switched. 2.The detection device according to claim 1, wherein the dangerous drivingdegree is determined depending on a duration of time between when thesignal indication is switched and when the acceleration data exceeds afirst threshold.
 3. The detection device according to claim 1, furthercomprising an acceleration sensor configured to acquire the accelerationdata of the vehicle.
 4. The detection device according to claim 1,further comprising a communication unit configured to transmit thedangerous driving degree detected by the detection unit to a serverapparatus including an evaluation unit configured to evaluate driving ofthe driver.
 5. The detection device according to claim 1, wherein thecamera acquires the image data in (R,G,B) color space, and therecognition unit converts the image data in the (R,G,B) color space intoimage data in (Y,U,V) color space and extracts a signal pixel regionrepresenting signal indication from the image data in the (Y,U,V) colorspace based on the image data in (Y,U,V) color space and (U,V)distributions of signal pixels representing signal indication which isobtained in advance.
 6. The detection device according to claim 5,wherein the recognition unit expands the signal pixel region into anexpanded pixel region by covering each pixel in the signal pixel regionwith a plurality of pixels and recognizes a circular pixel regionincluded in the expanded pixel region as a shape of the signalindication of the traffic signal.
 7. The detection device according toclaim 1, wherein when the detected dangerous driving degree is higherthan a second threshold, the detection unit alerts the driver of thevehicle that the driver is making dangerous driving.
 8. A detectionsystem comprising: a camera configured to acquire image data obtained bycapturing surroundings of a vehicle; a recognition unit configured torecognize switching of signal indication of a traffic signal from theimage data; a detection unit configured to detect a dangerous drivingdegree indicating a degree of dangerous driving done by a driver of thevehicle based on acceleration data of the vehicle acquired after thesignal indication is switched; a storage unit configured to storetherein the dangerous driving degree of the driver; and an evaluationunit configured to evaluate driving of the driver based on the dangerousdriving degree of the driver stored in the storage unit.
 9. A detectionmethod comprising: acquiring, by a camera, image data obtained bycapturing surroundings of a vehicle; recognizing, by a recognition unit,switching of signal indication of a traffic signal from the image data;and detecting, by a detection unit, a dangerous driving degreeindicating a degree of dangerous driving done by a driver of the vehiclebased on acceleration data of the vehicle acquired after the signalindication is switched.